Angewandte Datenverarbeitung und Visualisierung (WiSe23/24)
  • D. Palleschi
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  1. 1  Syllabus
  • Preface
  • 1  Syllabus
  • 2  Kursübersicht
  • 3  Summary
  • References

1  Syllabus

The main aim of this course is to develop the knowledge and skills required to implement an “Exploratory Data Analysis (EDA)”. EDA is not a formal process with specific rules, but is rather “a state of mind” (wickham_r_nodate?, Ch. 11). The knowledge required to carry out an EDA is simply understanding your data and how to explore its structure to get an understanding for its distribution and patterns. The skills required to carry out an EDA are specific to the language used to conduct your EDA, which in our case is R.

Woche Datum Topic Materials
1 2023-10-18 Intro to R @wickham_r_nodate, Ch. 1 & 3
2 2023-10-25 Data Viz 1
3 2023-11-01 Wrangling 1
4 2023-11-08 Dynamic Reports with Quarto
5 2023-11-15 Descriptive statistics
6 2023-11-22 Workflow 1
7 2023-11-29 Bericht 1
8 2023-12-06 Dateneinlesung
9 2023-12-13 Wrangling 2
10 2023-12-20 Data Viz 2
Vorlesungsfrei 2023-12-27 Vorlesungsfrei Vorlesungsfrei
Vorlesungsfrei 2024-01-03 Vorlesungsfrei Vorlesungsfrei
11 2024-01-10 Bericht 2
12 2024-01-17
13 2024-01-24
14 2024-01-31 Bericht 3
15 2024-02-07
16 2024-02-14
Preface
2  Kursübersicht
Source Code
---
title: "Syllabus"
execute:
  echo: false
---

The main aim of this course is to develop the knowledge and skills required to implement an "Exploratory Data Analysis (EDA)". EDA is not a formal process with specific rules, but is rather "a state of mind" [@wickham_r_nodate, Ch. 11]. The knowledge required to carry out an EDA is simply understanding your data and how to explore its structure to get an understanding for its distribution and patterns. The skills required to carry out an EDA are specific to the language used to conduct your EDA, which in our case is R.

```{r}
pacman::p_load(dplyr,
               lubridate,
               gt,
               timesaveR)
```


```{r}
#| eval: false

# Create syllabus structure ####

# define negative %in%; don't end up using this I think
'%ni%' <- Negate("%in%")

# create tibble containing all weekly dates from first lecture until last
dates <- tibble(
  Datum = as.character(seq(ymd("2023-10-18"), ymd("2024-2-14"), by = "weeks")))

# create vector with dates of holidays
holidays <- c("2024-01-03",
              "2023-12-27" )

# remove holiday dates and add Woche, which lists the week number
syllabus <-
  dates |> 
  mutate(class = ifelse(Datum %in% holidays, "Vorlesungsfrei", "class")) |> 
  mutate(Woche = 1:length(Datum), .by = class, .before = Datum) |> 
  mutate(Woche = ifelse(Datum %in% holidays, "Vorlesungsfrei", Woche)) |> 
  select(-class) |> 
  mutate(Topic = ifelse(Datum %in% holidays, "Vorlesungsfrei", ""),
         Materials = ifelse(Datum %in% holidays, "Vorlesungsfrei", ""))

# now print as tribble, copy and paste, and add "Topic
to_tribble(syllabus, show = T)
```

```{r}
tribble(
  ~ Woche,            ~ Datum,        ~ Topic,            ~ Materials,
  "1",               "2023-10-18",  "Intro to R",   "@wickham_r_nodate, Ch. 1 & 3",
  "2",               "2023-10-25",  "Data Viz 1", "",
  "3",               "2023-11-01",  "Wrangling 1", "",
  "4",               "2023-11-08",  "Dynamic Reports with Quarto", "",
  "5",               "2023-11-15",  "Descriptive statistics", "",
  "6",               "2023-11-22",  "Workflow 1", "",
  "7",               "2023-11-29", "Bericht 1", "",
  "8",               "2023-12-06", "Dateneinlesung", "",
  "9",               "2023-12-13", "Wrangling 2", "",
  "10",              "2023-12-20", "Data Viz 2", "",
  "Vorlesungsfrei",  "2023-12-27",  "Vorlesungsfrei",  "Vorlesungsfrei",
  "Vorlesungsfrei",  "2024-01-03",  "Vorlesungsfrei",  "Vorlesungsfrei",
  "11",              "2024-01-10",  "Bericht 2", "",
  "12",              "2024-01-17", "", "",
  "13",              "2024-01-24", "", "",
  "14",              "2024-01-31", "Bericht 3", "",
  "15",              "2024-02-07", "", "",
  "16",              "2024-02-14", "", ""
) |> 
  gt()
```